EP3953691A4 - Methods and systems for crack detection using a fully convolutional network - Google Patents

Methods and systems for crack detection using a fully convolutional network Download PDF

Info

Publication number
EP3953691A4
EP3953691A4 EP20788330.7A EP20788330A EP3953691A4 EP 3953691 A4 EP3953691 A4 EP 3953691A4 EP 20788330 A EP20788330 A EP 20788330A EP 3953691 A4 EP3953691 A4 EP 3953691A4
Authority
EP
European Patent Office
Prior art keywords
systems
methods
crack detection
convolutional network
fully convolutional
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP20788330.7A
Other languages
German (de)
French (fr)
Other versions
EP3953691A1 (en
Inventor
Fu-Chen Chen
Mohammad R JAHANSHAHI
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Purdue Research Foundation
Original Assignee
Purdue Research Foundation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Purdue Research Foundation filed Critical Purdue Research Foundation
Publication of EP3953691A1 publication Critical patent/EP3953691A1/en
Publication of EP3953691A4 publication Critical patent/EP3953691A4/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/9515—Objects of complex shape, e.g. examined with use of a surface follower device
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G06F18/24133—Distances to prototypes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
    • G06F18/256—Fusion techniques of classification results, e.g. of results related to same input data of results relating to different input data, e.g. multimodal recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G06T7/38—Registration of image sequences
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8854—Grading and classifying of flaws
    • G01N2021/8861—Determining coordinates of flaws
    • G01N2021/8864—Mapping zones of defects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8883—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges involving the calculation of gauges, generating models
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/9515—Objects of complex shape, e.g. examined with use of a surface follower device
    • G01N2021/9518—Objects of complex shape, e.g. examined with use of a surface follower device using a surface follower, e.g. robot
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30132—Masonry; Concrete
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30181—Earth observation
    • G06T2207/30184—Infrastructure
EP20788330.7A 2019-04-09 2020-04-09 Methods and systems for crack detection using a fully convolutional network Pending EP3953691A4 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201962831297P 2019-04-09 2019-04-09
PCT/US2020/027488 WO2020210506A1 (en) 2019-04-09 2020-04-09 Methods and systems for crack detection using a fully convolutional network

Publications (2)

Publication Number Publication Date
EP3953691A1 EP3953691A1 (en) 2022-02-16
EP3953691A4 true EP3953691A4 (en) 2023-06-07

Family

ID=72750837

Family Applications (1)

Application Number Title Priority Date Filing Date
EP20788330.7A Pending EP3953691A4 (en) 2019-04-09 2020-04-09 Methods and systems for crack detection using a fully convolutional network

Country Status (5)

Country Link
US (1) US20220172346A1 (en)
EP (1) EP3953691A4 (en)
AU (1) AU2020272936B2 (en)
CA (1) CA3136674C (en)
WO (1) WO2020210506A1 (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11836912B2 (en) * 2020-09-22 2023-12-05 Future Dial, Inc. Grading cosmetic appearance of a test object based on multi-region determination of cosmetic defects
US11900581B2 (en) 2020-09-22 2024-02-13 Future Dial, Inc. Cosmetic inspection system
CN115326809B (en) * 2022-08-02 2023-06-06 山西省智慧交通研究院有限公司 Tunnel lining apparent crack detection method and detection device
CN115620210B (en) * 2022-11-29 2023-03-21 广东祥利科技有限公司 Method and system for determining performance of electronic wire material based on image processing

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10248770B2 (en) * 2014-03-17 2019-04-02 Sensory, Incorporated Unobtrusive verification of user identity
US10846672B2 (en) * 2015-05-12 2020-11-24 A La Carte Media, Inc. Kiosks for remote collection of electronic devices for value, and associated mobile application for enhanced diagnostics and services
US10360477B2 (en) * 2016-01-11 2019-07-23 Kla-Tencor Corp. Accelerating semiconductor-related computations using learning based models
US10824145B1 (en) * 2016-01-22 2020-11-03 State Farm Mutual Automobile Insurance Company Autonomous vehicle component maintenance and repair
JP6083057B1 (en) * 2016-07-21 2017-02-22 株式会社Ｃｑ−Ｓネット Status detector using standing wave radar
GB201704373D0 (en) * 2017-03-20 2017-05-03 Rolls-Royce Ltd Surface defect detection
US10445871B2 (en) * 2017-05-22 2019-10-15 General Electric Company Image analysis neural network systems
WO2018216629A1 (en) * 2017-05-22 2018-11-29 キヤノン株式会社 Information processing device, information processing method, and program
KR101822963B1 (en) * 2017-07-25 2018-01-31 한국생산기술연구원 An Apparatus and A Method For Detecting A Defect Based On Binary Images
JP6626057B2 (en) * 2017-09-27 2019-12-25 ファナック株式会社 Inspection device and inspection system

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
CHEN FU-CHEN ET AL: "NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion", IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, IEEE SERVICE CENTER, PISCATAWAY, NJ, USA, vol. 65, no. 5, 1 May 2018 (2018-05-01), pages 4392 - 4400, XP011676060, ISSN: 0278-0046, [retrieved on 20180116], DOI: 10.1109/TIE.2017.2764844 *
CHEN FU-CHEN ET AL: "NB-FCN: Real-Time Accurate Crack Detection in Inspection Videos Using Deep Fully Convolutional Network and Parametric Data Fusion", IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, IEEE, USA, vol. 69, no. 8, 20 December 2019 (2019-12-20), pages 5325 - 5334, XP011794866, ISSN: 0018-9456, [retrieved on 20200623], DOI: 10.1109/TIM.2019.2959292 *
CHEN FU-CHEN ET AL: "Video-based crack detection using deep learning and Nave Bayes data fusion", PROCEEDINGS OF SPIE; [PROCEEDINGS OF SPIE ISSN 0277-786X VOLUME 10524], SPIE, US, vol. 10598, 27 March 2018 (2018-03-27), pages 105980J - 105980J, XP060105883, ISBN: 978-1-5106-1533-5, DOI: 10.1117/12.2296772 *
PARK SOMIN ET AL: "Patch-based crack detection in black box road images using deep learning", 35TH INTERNATIONAL SYMPOSIUM ON AUTOMATION AND ROBOTICS IN CONSTRUCTION (ISARC 2018); BERLIN, GERMANY; JULY 22-25, 2018,, vol. 35, 30 November 2017 (2017-11-30), pages 1 - 4, XP009537879, ISBN: 978-3-00-060855-1, DOI: 10.22260/ISARC2018/0104 *
SPENCER BILLIE F. ET AL: "Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring", ENGINEERING, vol. 5, no. 2, 1 April 2019 (2019-04-01), pages 199 - 222, XP093036206, ISSN: 2095-8099, DOI: 10.1016/j.eng.2018.11.030 *

Also Published As

Publication number Publication date
EP3953691A1 (en) 2022-02-16
US20220172346A1 (en) 2022-06-02
CA3136674A1 (en) 2020-10-15
AU2020272936B2 (en) 2023-08-17
AU2020272936A1 (en) 2021-11-04
CA3136674C (en) 2024-02-13
WO2020210506A1 (en) 2020-10-15

Similar Documents

Publication Publication Date Title
EP3953843A4 (en) Systems and methods for end-to-end architectures for voice spoofing detection
EP3953691A4 (en) Methods and systems for crack detection using a fully convolutional network
EP3821586A4 (en) Systems and methods for secure custodial service
EP3834134A4 (en) Method and system for performing object detection using a convolutional neural network
EP3959517A4 (en) Method and system for detecting a structural anomaly in a pipeline network
EP4000753A4 (en) Sorting system and method
EP3968683A4 (en) Method and device for grading network system
EP3918274A4 (en) Object dimensioning system and method
EP3952363A4 (en) Method for dealing with network failure
EP4065890A4 (en) A system and method for pyrolysis
EP3688620A4 (en) System and method for blockchain-based notification
EP4022253A4 (en) Positioning systems and methods
EP3920126A4 (en) Harmful act detection system and method
EP3984010A4 (en) Systems and methods for object monitoring
EP3688702A4 (en) System and method for blockchain-based notification
EP3859624A4 (en) Received order management system, received order management method, and program
EP3977814A4 (en) Systems and methods for monitoring movements
EP3984175A4 (en) Network recovery systems and methods
EP4028759A4 (en) System and method for testing a surface
EP4027542A4 (en) Line sequence detection method and detection system
EP3901784A4 (en) Patent evaluation method and system
EP4064977A4 (en) Systems, devices, and methods for sensor communications
EP4030373A4 (en) Object comparison method, and device
EP3982291A4 (en) Object pick and place detection system, method and apparatus
EP3998577A4 (en) Object detection device, object detection method, and program

Legal Events

Date Code Title Description
STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE

PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20211013

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

DAV Request for validation of the european patent (deleted)
DAX Request for extension of the european patent (deleted)
A4 Supplementary search report drawn up and despatched

Effective date: 20230508

RIC1 Information provided on ipc code assigned before grant

Ipc: G06N 3/08 20060101ALI20230428BHEP

Ipc: G06T 7/00 20170101ALI20230428BHEP

Ipc: G01N 21/88 20060101AFI20230428BHEP